1. Those Who Make Money and Those Who Lose Money
Do you often reflect this way: "This investment turned a profit—why did it make money? What did I do right?" or "This trade lost money—why did it lose? What did I do wrong?"
But endlessly reviewing the past will never yield real results.
Making money can easily give one the illusion: "I've made money, so my judgment must be right, and this approach must be effective." In reality, a single profitable trade may involve a large element of luck—for example:
Trade 1: Stock A, purchased one month ago, has risen by 30%.
Reason for Buy: Bullish on the industry trend of XXX.
Post‑mortem attribution: I correctly identified the industry trend, so I made a profit.
The actual reason for the price increase: The company is implementing an equity‑based incentive plan, which creates upward pressure on the stock price, and it has been releasing a series of positive developments to institutional investors.
For losing trades, it's even less appropriate to simply ask, "Why did I lose?" For example:
Trade 2: Stock B—after buying, it plunged 8% at the open the next day, leaving me trapped.
Reason for buying: The stock has held up well amid a sharp market plunge, and I expect it to perform strongly during the next day's rebound, aiming to capture a short-term price spread.
Review and summarize lessons learned: During a sharp market plunge, strong-performing stocks are merely being used by major players to lure buyers.
The underlying reason: The stock held up well during the plunge because large institutional investors were bullish and stepped in to buy. However, after the market reopened that evening, they judged the broader market to be weakening and pulled out, triggering a sharp sell-off the next day as traders triggered stop-loss orders.
When we engage in this kind of post‑trade review, it's all too easy to start doubting a well‑established strategy after just one or two losses. In psychology, this phenomenon is known as the "recency effect," whereby people's impressions are disproportionately shaped by the most recent events.
Only when you begin systematically analyzing a category of decisions—rather than merely interpreting a single outcome—can luck gradually be stripped away from the post‑mortem process. The true purpose of such analysis is to refine and strengthen your investment methodology; the right approach is to distinguish between trades that generate profits and those that result in losses:
In profit‑driving investments, the key is to focus on what can be replicated.
For losing investments, the key focus is on analyzing and identifying the risks that led to the mistakes.
Therefore, the retrospective method can also be divided into two phases:
Before developing a mature investment approach, only review investments that turned a profit.
Once a mature investment approach has been established, the focus shifts to reviewing and analyzing losing investments.
2. Review successful investments and develop strategies.
A post‑mortem is not a summary or an awards ceremony; it's about replicating lessons learned and evaluating how a single investment fits within a portfolio of similar ones. The real question is: if, going forward, we were to make 20 more purchases for the same reason, could we still generate profits in most cases?
Before developing a mature investment approach, focus on reviewing only the investments that generated profits. Rather than analyzing each one individually, accumulate these cases and synthesize them to identify any common patterns, which can then be distilled into replicable strategies.
So the best approach is to review your past trading records, systematically compiling all the investments that generated profits. Don't just note when you bought, what you purchased, and how much you earned; also document why you made those trades, how you executed them, and when you decided to sell.
Specifically, you need to assign tags to each profitable trade; these tags fall into two categories:
The first category is stock fundamental tags, which include:
Industry characteristics (technology, consumer goods, or cyclical) and the level of economic prosperity.
Is the company's performance growing, expected to grow, showing no significant change, or are you indifferent to its performance?
Where does the valuation stand in historical context?
What is the market's core expectation at the time of purchase?
Is the catalyst fundamental or thematic? Is it short-term or medium-term?
What's the core rationale for buying?
Is the reason for selling or reducing holdings a shift in underlying logic, the realization of a catalyst, overvaluation, or other uses of capital?
Do you think the money ultimately earned comes mainly from valuation gains, earnings growth, or simply market sentiment?
(If the focus is on technical analysis, you can list the criteria for technical analysis; no further elaboration is needed here.)
Here, it is especially important to document "what I believed would happen in the future at the time," rather than retrospectively writing "what actually ended up happening." You can also note whether that prediction ultimately came true.
The second category comprises trading customs and details, including:
Should you buy on the right side (chasing after a price rally) or on the left side (gradually accumulating during the bottom‑formation phase)?
What's your position size? Will you buy the full amount in one go, or build up gradually in stages? Do you have any unplanned additional positions added along the way?
How long have you held it? Has it been for the planned duration?
At what profit level do you start reducing your position, and did you first cut losses before re-entering?
Have you ever changed your plans due to short-term fluctuations?
It can even capture very granular details, such as the mindset during position building, price rallies, mid‑trade pullbacks, and sell‑off moments.
The fundamentals tab tells you which stocks are likely to generate profits, while the trading tab shows you how to trade more effectively to maximize your earnings.
In most cases, seemingly unrelated transactions invariably share a common pattern: they are executed when the industry is at an inflection point and the market has yet to fully price in the shift. This recurring structural feature warrants separate analysis.
There is no one-size-fits-all "holy grail" in investing, but each investor does have their own—often shaped by their skills and personality, knowledge base, risk tolerance, financial situation, and investment goals. Repeatedly generating returns with the same approach typically reflects a method you've unconsciously refined over time—a personal holy grail that may not work for others, just as the strategies others use may not yield the same results for you.
For example, if you've noticed that your most profitable trades in the past have all occurred during phases when "industry sentiment has just begun to turn around, yet the market hasn't fully priced it in," it's likely because you're highly attuned to subtle yet pivotal shifts in fundamentals—making you well-suited to capitalize on such opportunities. However, this overly sensitive temperament may not serve you well when holding stocks in sectors already experiencing strong prosperity, as these often exhibit significant data volatility; an excessively sensitive investor might jump ship at the slightest fluctuation.
Once you've identified these "one‑trick‑pony" approaches, your next step should be to deliberately seek out more opportunities that meet the same criteria, then replicate, validate, and fine-tune them.
First, let's reflect: What exactly did you observe at the time when those investments were profitable? Could that signal have been identified in advance? Were there clear entry criteria? You need to transform your vague "I had a good feeling back then" into specific, measurable conditions—turning what was once purely based on experience into a systematic framework for identifying your next opportunity.
Next comes validation: you can proactively sift through the market to identify opportunities where "industry sentiment has just turned around but the market has yet to fully price them in," and see whether similar signals emerge, assessing whether this approach can help you consistently pick winning stocks.
There are also transaction terms—can they, too, be partially replicated from successful cases?
At this stage, the most important thing isn't to craft a perfectly polished methodology; it's to keep conducting small‑scale tests. You might even log those stocks that "seemed to meet your criteria but ultimately didn't buy," and then track how they performed afterward.
After a dozen or even dozens of such observations, you will gradually come to discern which conditions are truly critical, which are merely incidental factors that happened to arise at the time, and under what circumstances this approach will fail.
So‑called investment approaches are seldom distilled from a single post‑mortem; rather, they emerge gradually, refined through the ongoing process of identifying and evaluating similar opportunities.
Of course, no investment approach is guaranteed to be consistently profitable, and Buffett's success rate doesn't exceed 60% either. The element of chance in investing will always remain. When faced with investments that seem to meet all the criteria yet still end in losses, that's when you enter the second stage of post‑mortem analysis.
3. Review losing investments and identify risks.
Many investors have had this experience: a strategy distilled from past successes works well for a few trades, boosting their confidence. Yet this time, all the expected signals materialize, the buy order has already been executed, and the fundamentals align with your expectations—still, the stock refuses to rise. You re‑examine the fundamentals thoroughly and review your own actions, finding no flaws. Convinced that this is a test—and an opportunity—from above, you rally yourself with the mantra, "Mr. Market has made another mistake," double your position, and turn what was a routine loss into a major trapped‑in‑the‑stock situation.
Or there's another mindset: after failing two or three times in a row, they simply give up on that approach.
No investment strategy can consistently generate profits; every approach will inevitably reach a point where it ceases to be effective. Therefore, it's crucial to understand the circumstances under which such strategies may fail. Once you've developed a mature investment methodology, the next step is to identify the boundaries of its applicability.
After investors develop a successful, replicable strategy, most losses stem from errors in the replication process—each arising from distinct, specific risk events.
For example, suppose you've developed a strategy of buying when industry sentiment reverses and valuations are at low levels. A common reason for failure is misjudging the cyclical upturn: such a reversal is actually a low-probability event, and during that time, a cascade of adverse developments can unfold in the company's operations—earnings deteriorate, the stock price remains depressed, employee‑incentive programs falter, key talent departs, product quality becomes inconsistent, channel inventories pile up, distributors engage in diversionary sales, bargaining power with upstream suppliers erodes, and competitors launch a price war…
The longer a company's business conditions remain on a downward trajectory, the harder it becomes to reverse the trend; achieving a 50% success rate would already be commendable. What's often labeled as a "reversal" is usually just a short-lived rebound driven by localized operational adjustments—far from the rosy picture one might expect.
It may be that the company's own operations are picking up, but the industry remains sluggish, prompting competitors to engage in price wars and dragging profits back into a quagmire.
Alternatively, before the industry recovers, a company might suddenly write off all its bad debts accumulated over the past few years, triggering an unexpected "time bomb."
Or perhaps the company has turned a corner—you've got it right—but the broader market is underperforming, keeping valuations suppressed.
Alternatively, even if you've correctly identified a company's turnaround and the broader market is performing well, if the prevailing market style isn't aligned, your purchase may still be somewhat overpriced.
Alternatively, companies may be undergoing aggressive transformations that require substantial financing, thereby putting downward pressure on their stock prices…
Risk is always specific and individual; until you experience it, you never know what the next one will be.
Therefore, a mature strategy does not require you to eliminate all losses in advance; rather, it calls for distinguishing between losses that are part of the strategy's inherent volatility and those that stem from exceptional risks outside the strategy's applicable boundaries.
The former requires time to endure, while the latter can be identified and avoided mid‑process, though losses cannot be entirely prevented.
Soros says that whether a bet is right or wrong is irrelevant; what matters is maximizing gains on winning bets and minimizing losses on losing ones—achieved, in the latter case, by "identifying fundamental risks mid‑trade and exiting early." This is an essential skill for any investment approach.
Therefore, at this stage, as long as your decision‑making criteria align with the strategy, avoid asking yourself why you lost this time or hastily questioning the strategy itself. Instead, meticulously document this loss and analyze which specific assumption of the strategy was violated, turning it into a stop‑loss condition that can inform future decisions.
Moreover, treat each loss as a stress test for your strategy, and assess what its maximum potential drawdown might be.
In summary, each losing investment should be thoroughly reviewed to identify its risk factors—especially those with low probability. The end result is not a "failure‑avoidance strategy," but rather a map of the potential pitfalls associated with that strategy.
4. Strategy Library and Risk Library
To summarize the approach to post-event review:
1. In the first phase, identify commonalities across profitable projects, develop a systematic approach, and continuously test new cases to refine your strategy.
2. In the second phase, identify discrepancies among loss-making projects, assess risks, and refine strategy boundaries.
The effectiveness of a strategy often depends on market conditions; therefore, a seasoned investor typically employs multiple strategies, each of which must undergo this same process.
Ultimately, you'll build a strategy library and a corresponding risk library. The key to sustained profitability lies in leveraging the strategy library to generate returns while using the risk library to mitigate drawdowns.
It's not just about investment; many highly uncertain endeavors—such as entrepreneurship, innovation, experimentation, and high‑stakes projects—are all the same: the value of success lies in replication, while the value of failure lies in risk mitigation. Successful lessons should be continually abstracted, whereas lessons from failure must be repeatedly concretized.
Editor: jayden